Bayesian & Probabilistic

Restricted Boltzmann machines modeling human choice NeurIPS 2014 Revisiting Bayesian Blind Deconvolution JMLR 2014 Robust Bayesian Max-Margin Clustering NeurIPS 2014 Robust learning of inhomogeneous PMMs AISTATS 2014 Robust Principal Component Analysis with Complex Noise ICML 2014 Sample Efficient Reinforcement Learning with Gaussian Processes ICML 2014 Sampling for Inference in Probabilistic Models with Fast Bayesian Quadrature NeurIPS 2014 Scalable and Robust Bayesian Inference via the Median Posterior ICML 2014 Scalable Bayesian Low-Rank Decomposition of Incomplete Multiway Tensors ICML 2014 Scalable Collaborative Bayesian Preference Learning AISTATS 2014 Scalable Inference for Neuronal Connectivity from Calcium Imaging NeurIPS 2014 Scaling-up Importance Sampling for Markov Logic Networks NeurIPS 2014 Semi-Separable Hamiltonian Monte Carlo for Inference in Bayesian Hierarchical Models NeurIPS 2014 Sequential Monte Carlo for Graphical Models NeurIPS 2014 Signal Aggregate Constraints in Additive Factorial HMMs, with Application to Energy Disaggregation NeurIPS 2014 Simple MAP Inference via Low-Rank Relaxations NeurIPS 2014 Skip Context Tree Switching ICML 2014 SMERED: A Bayesian Approach to Graphical Record Linkage and De-duplication AISTATS 2014 Smoothed Gradients for Stochastic Variational Inference NeurIPS 2014 Sparse Bayesian structure learning with “dependent relevance determination” priors NeurIPS 2014 Sparse Bayesian Variable Selection for the Identification of Antigenic Variability in the Foot-and-Mouth Disease Virus AISTATS 2014 Sparse meta-Gaussian information bottleneck ICML 2014 Spatio-temporal Representations of Uncertainty in Spiking Neural Networks NeurIPS 2014 Spectral Learning of Mixture of Hidden Markov Models NeurIPS 2014 Spectral Methods for Indian Buffet Process Inference NeurIPS 2014